[Objective] This study aims to analyze the spatiotemporal distribution and probabilistic characteristics of multi-level meteorological droughts at the seasonal scale in Guangxi， China， with a focus on seasonal continuous drought events. The study quantitatively analyzes drought frequency trends， identifies the optimal probability distribution function for seasonal precipitation， and assesses the joint probability of consecutive seasonal droughts with the goal of providing more scientific basis for drought risk management in Guangxi. [Methods] Using daily precipitation data from 18 meteorological stations （1960-2020）， we calculated the Standardized Precipitation Index （SPI） for four seasonal scales and classified drought thresholds into four levels （mild， moderate， severe， and extreme）. The GAMLSS （Generalized Additive Models for Location， Scale and Shape） model compared six probability distributions （Gamma， Normal， Lognormal， Gumbel， Weibull， and Logistic） to fit precipitation sequences， and the Gamma function was selected as the optimal model based on the AIC （Akaike Information Criterion）. Five Copula functions （Clayton， Frank， Gaussian， Gumbel， and t-Copula） were used to construct the joint distribution of continuous seasonal drought， and the optimal Copula function was determined using the squared Euclidean distance （OSL）. Spatial interpolation techniques were applied to visualize regional drought probabilities. [Results] The SPI in spring showed a decreasing trend （-0.005 8/a）， indicating an increase in drought frequency， while the SPI in summer （0.007 6/a）， autumn （0.002 1/a）， and winter （0.015 3/a） showed an increasing trend， indicating a decrease in drought frequency. Based on the fitting results of the GAMLSS model using six probability distribution functions for the seasonal precipitation series in Guangxi， the gamma function appeared most frequently in the optimal and suboptimal distributions， indicating that the gamma function can effectively describe the characteristics of precipitation changes. The seasonal frequencies of different drought levels at various stations show that mild droughts （30%-48%） are more common in summer， while moderate droughts （20%-37%）， severe droughts （10%-27%）， and extreme droughts （5%-17%） are more likely to occur in autumn. The gamma distribution performs exceptionally well， with the difference between theoretical and empirical frequencies not exceeding 11%. Different regions in Guangxi exhibit significant differences in consecutive drought characteristics. Among the four consecutive seasons of spring-summer， summer-autumn， autumn-winter， and winter-spring， the probability of consecutive droughts， moderate droughts， severe droughts， and extreme droughts is higher and more widespread during the winter-spring season. The probability range for consecutive winter-spring droughts is 13.1%-20.9%， primarily distributed in the southern coastal areas of Guangxi， central Guangxi， and northeastern Guangxi， with the highest probability of drought occurring in the northwestern part of Wuzhou City. Regions with a higher probability of severe consecutive droughts are distributed in Liuzhou， Laibin， Qinzhou， and Baise. Regions with a higher probability of severe and extreme consecutive droughts are distributed in Liuzhou， Laibin， Qinzhou， and Baise， among which Liuzhou has the highest probability of severe and extreme consecutive droughts during the spring-summer season， with probabilities of 7.1% and 3.9%， respectively. [Conclusions] The study revealed differences in seasonal drought trends in Guangxi， with spring becoming increasingly dry， while other seasons exhibit a trend toward greater moisture. The robustness of the gamma function in precipitation modeling highlights its practicality in drought frequency analysis. Crucially， the Copula-based joint probability analysis identified winter and spring as the most susceptible periods for consecutive droughts， particularly in regions dominated by karst topography. These findings provide scientific basis for adaptive drought management strategies， emphasizing the need to prioritize addressing composite drought risks in regional water resource planning.